Overview

Dataset statistics

Number of variables33
Number of observations3632
Missing cells347
Missing cells (%)0.3%
Total size in memory936.5 KiB
Average record size in memory264.0 B

Variable types

Text29
Numeric4

Alerts

games_played_current_season_flag has constant value ""Constant
draft_round has 146 (4.0%) missing valuesMissing
draft_number has 198 (5.5%) missing valuesMissing
person_id has unique valuesUnique
team_id has 597 (16.4%) zerosZeros

Reproduction

Analysis started2023-07-13 14:06:40.485413
Analysis finished2023-07-13 14:06:41.141959
Duration0.66 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

person_id
Text

UNIQUE 

Distinct3632
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:41.411510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.147577093
Min length1

Characters and Unicode

Total characters18696
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3632 ?
Unique (%)100.0%

Sample

1st row76001
2nd row76002
3rd row76003
4th row949
5th row76006
ValueCountFrequency (%)
76001 1
 
< 0.1%
944 1
 
< 0.1%
1626146 1
 
< 0.1%
1629061 1
 
< 0.1%
76003 1
 
< 0.1%
949 1
 
< 0.1%
76006 1
 
< 0.1%
76007 1
 
< 0.1%
203518 1
 
< 0.1%
1630173 1
 
< 0.1%
Other values (3622) 3622
99.7%
2023-07-13T22:06:41.767424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3395
18.2%
1 2396
12.8%
2 2348
12.6%
6 2241
12.0%
0 1903
10.2%
8 1587
8.5%
3 1466
7.8%
9 1157
 
6.2%
4 1118
 
6.0%
5 1085
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18696
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3395
18.2%
1 2396
12.8%
2 2348
12.6%
6 2241
12.0%
0 1903
10.2%
8 1587
8.5%
3 1466
7.8%
9 1157
 
6.2%
4 1118
 
6.0%
5 1085
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 18696
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3395
18.2%
1 2396
12.8%
2 2348
12.6%
6 2241
12.0%
0 1903
10.2%
8 1587
8.5%
3 1466
7.8%
9 1157
 
6.2%
4 1118
 
6.0%
5 1085
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3395
18.2%
1 2396
12.8%
2 2348
12.6%
6 2241
12.0%
0 1903
10.2%
8 1587
8.5%
3 1466
7.8%
9 1157
 
6.2%
4 1118
 
6.0%
5 1085
 
5.8%
Distinct1291
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:42.057643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length14
Median length10.5
Mean length5.008259912
Min length2

Characters and Unicode

Total characters18190
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique846 ?
Unique (%)23.3%

Sample

1st rowAlaa
2nd rowZaid
3rd rowKareem
4th rowShareef
5th rowForest
ValueCountFrequency (%)
john 81
 
2.2%
bob 59
 
1.6%
jim 52
 
1.4%
mike 52
 
1.4%
chris 43
 
1.2%
bill 34
 
0.9%
joe 32
 
0.9%
tom 30
 
0.8%
george 29
 
0.8%
paul 28
 
0.8%
Other values (1280) 3207
87.9%
2023-07-13T22:06:42.394707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1855
 
10.2%
a 1555
 
8.5%
n 1424
 
7.8%
r 1365
 
7.5%
i 1205
 
6.6%
o 1196
 
6.6%
l 891
 
4.9%
y 576
 
3.2%
J 572
 
3.1%
h 519
 
2.9%
Other values (47) 7032
38.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14359
78.9%
Uppercase Letter 3734
 
20.5%
Other Punctuation 79
 
0.4%
Space Separator 15
 
0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1855
12.9%
a 1555
10.8%
n 1424
9.9%
r 1365
9.5%
i 1205
 
8.4%
o 1196
 
8.3%
l 891
 
6.2%
y 576
 
4.0%
h 519
 
3.6%
t 518
 
3.6%
Other values (16) 3255
22.7%
Uppercase Letter
ValueCountFrequency (%)
J 572
15.3%
D 345
 
9.2%
M 305
 
8.2%
B 257
 
6.9%
R 252
 
6.7%
C 238
 
6.4%
T 218
 
5.8%
A 215
 
5.8%
S 189
 
5.1%
K 155
 
4.2%
Other values (16) 988
26.5%
Other Punctuation
ValueCountFrequency (%)
. 68
86.1%
' 9
 
11.4%
, 2
 
2.5%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18093
99.5%
Common 97
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1855
 
10.3%
a 1555
 
8.6%
n 1424
 
7.9%
r 1365
 
7.5%
i 1205
 
6.7%
o 1196
 
6.6%
l 891
 
4.9%
y 576
 
3.2%
J 572
 
3.2%
h 519
 
2.9%
Other values (42) 6935
38.3%
Common
ValueCountFrequency (%)
. 68
70.1%
15
 
15.5%
' 9
 
9.3%
- 3
 
3.1%
, 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1855
 
10.2%
a 1555
 
8.5%
n 1424
 
7.8%
r 1365
 
7.5%
i 1205
 
6.6%
o 1196
 
6.6%
l 891
 
4.9%
y 576
 
3.2%
J 572
 
3.1%
h 519
 
2.9%
Other values (47) 7032
38.7%
Distinct2308
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:42.674663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length16
Median length14
Mean length6.557819383
Min length2

Characters and Unicode

Total characters23818
Distinct characters55
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1883 ?
Unique (%)51.8%

Sample

1st rowAbdelnaby
2nd rowAbdul-Aziz
3rd rowAbdul-Jabbar
4th rowAbdur-Rahim
5th rowAble
ValueCountFrequency (%)
williams 73
 
2.0%
smith 58
 
1.6%
johnson 39
 
1.1%
jones 38
 
1.0%
jr 33
 
0.9%
brown 27
 
0.7%
davis 26
 
0.7%
thomas 24
 
0.6%
robinson 24
 
0.6%
white 20
 
0.5%
Other values (2269) 3335
90.2%
2023-07-13T22:06:43.020352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2233
 
9.4%
n 1838
 
7.7%
a 1815
 
7.6%
r 1742
 
7.3%
o 1704
 
7.2%
i 1558
 
6.5%
l 1417
 
5.9%
s 1323
 
5.6%
t 978
 
4.1%
h 658
 
2.8%
Other values (45) 8552
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19802
83.1%
Uppercase Letter 3873
 
16.3%
Space Separator 65
 
0.3%
Other Punctuation 56
 
0.2%
Dash Punctuation 22
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2233
11.3%
n 1838
9.3%
a 1815
9.2%
r 1742
 
8.8%
o 1704
 
8.6%
i 1558
 
7.9%
l 1417
 
7.2%
s 1323
 
6.7%
t 978
 
4.9%
h 658
 
3.3%
Other values (16) 4536
22.9%
Uppercase Letter
ValueCountFrequency (%)
S 412
 
10.6%
M 368
 
9.5%
W 350
 
9.0%
B 319
 
8.2%
R 247
 
6.4%
C 216
 
5.6%
H 203
 
5.2%
P 195
 
5.0%
T 180
 
4.6%
J 173
 
4.5%
Other values (15) 1210
31.2%
Other Punctuation
ValueCountFrequency (%)
. 34
60.7%
' 22
39.3%
Space Separator
ValueCountFrequency (%)
65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23675
99.4%
Common 143
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2233
 
9.4%
n 1838
 
7.8%
a 1815
 
7.7%
r 1742
 
7.4%
o 1704
 
7.2%
i 1558
 
6.6%
l 1417
 
6.0%
s 1323
 
5.6%
t 978
 
4.1%
h 658
 
2.8%
Other values (41) 8409
35.5%
Common
ValueCountFrequency (%)
65
45.5%
. 34
23.8%
' 22
 
15.4%
- 22
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2233
 
9.4%
n 1838
 
7.7%
a 1815
 
7.6%
r 1742
 
7.3%
o 1704
 
7.2%
i 1558
 
6.5%
l 1417
 
5.9%
s 1323
 
5.6%
t 978
 
4.1%
h 658
 
2.8%
Other values (45) 8552
35.9%
Distinct3608
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:43.356219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.56415198
Min length5

Characters and Unicode

Total characters45633
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3585 ?
Unique (%)98.7%

Sample

1st rowAlaa Abdelnaby
2nd rowZaid Abdul-Aziz
3rd rowKareem Abdul-Jabbar
4th rowShareef Abdur-Rahim
5th rowForest Able
ValueCountFrequency (%)
john 81
 
1.1%
williams 73
 
1.0%
bob 59
 
0.8%
smith 58
 
0.8%
mike 52
 
0.7%
jim 52
 
0.7%
chris 43
 
0.6%
johnson 39
 
0.5%
jones 38
 
0.5%
bill 34
 
0.5%
Other values (3406) 6815
92.8%
2023-07-13T22:06:43.780734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4086
 
9.0%
3712
 
8.1%
a 3371
 
7.4%
n 3261
 
7.1%
r 3107
 
6.8%
o 2900
 
6.4%
i 2762
 
6.1%
l 2308
 
5.1%
s 1802
 
3.9%
t 1496
 
3.3%
Other values (47) 16828
36.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34156
74.8%
Uppercase Letter 7606
 
16.7%
Space Separator 3712
 
8.1%
Other Punctuation 135
 
0.3%
Dash Punctuation 24
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4086
12.0%
a 3371
9.9%
n 3261
9.5%
r 3107
 
9.1%
o 2900
 
8.5%
i 2762
 
8.1%
l 2308
 
6.8%
s 1802
 
5.3%
t 1496
 
4.4%
h 1177
 
3.4%
Other values (16) 7886
23.1%
Uppercase Letter
ValueCountFrequency (%)
J 744
 
9.8%
M 673
 
8.8%
S 601
 
7.9%
B 576
 
7.6%
R 499
 
6.6%
D 497
 
6.5%
C 454
 
6.0%
W 439
 
5.8%
T 398
 
5.2%
A 330
 
4.3%
Other values (16) 2395
31.5%
Other Punctuation
ValueCountFrequency (%)
. 102
75.6%
' 31
 
23.0%
, 2
 
1.5%
Space Separator
ValueCountFrequency (%)
3712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41762
91.5%
Common 3871
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4086
 
9.8%
a 3371
 
8.1%
n 3261
 
7.8%
r 3107
 
7.4%
o 2900
 
6.9%
i 2762
 
6.6%
l 2308
 
5.5%
s 1802
 
4.3%
t 1496
 
3.6%
h 1177
 
2.8%
Other values (42) 15492
37.1%
Common
ValueCountFrequency (%)
3712
95.9%
. 102
 
2.6%
' 31
 
0.8%
- 24
 
0.6%
, 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45633
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4086
 
9.0%
3712
 
8.1%
a 3371
 
7.4%
n 3261
 
7.1%
r 3107
 
6.8%
o 2900
 
6.4%
i 2762
 
6.1%
l 2308
 
5.1%
s 1802
 
3.9%
t 1496
 
3.3%
Other values (47) 16828
36.9%
Distinct3608
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:44.193402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length23
Mean length13.56332599
Min length6

Characters and Unicode

Total characters49262
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3585 ?
Unique (%)98.7%

Sample

1st rowAbdelnaby, Alaa
2nd rowAbdul-Aziz, Zaid
3rd rowAbdul-Jabbar, Kareem
4th rowAbdur-Rahim, Shareef
5th rowAble, Forest
ValueCountFrequency (%)
john 81
 
1.1%
williams 73
 
1.0%
bob 59
 
0.8%
smith 58
 
0.8%
jim 52
 
0.7%
mike 52
 
0.7%
chris 43
 
0.6%
johnson 39
 
0.5%
jones 38
 
0.5%
jr 34
 
0.5%
Other values (3406) 6815
92.8%
2023-07-13T22:06:44.638844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4086
 
8.3%
3712
 
7.5%
, 3631
 
7.4%
a 3371
 
6.8%
n 3261
 
6.6%
r 3107
 
6.3%
o 2900
 
5.9%
i 2762
 
5.6%
l 2308
 
4.7%
s 1802
 
3.7%
Other values (47) 18322
37.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34156
69.3%
Uppercase Letter 7606
 
15.4%
Other Punctuation 3764
 
7.6%
Space Separator 3712
 
7.5%
Dash Punctuation 24
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4086
12.0%
a 3371
9.9%
n 3261
9.5%
r 3107
 
9.1%
o 2900
 
8.5%
i 2762
 
8.1%
l 2308
 
6.8%
s 1802
 
5.3%
t 1496
 
4.4%
h 1177
 
3.4%
Other values (16) 7886
23.1%
Uppercase Letter
ValueCountFrequency (%)
J 744
 
9.8%
M 673
 
8.8%
S 601
 
7.9%
B 576
 
7.6%
R 499
 
6.6%
D 497
 
6.5%
C 454
 
6.0%
W 439
 
5.8%
T 398
 
5.2%
A 330
 
4.3%
Other values (16) 2395
31.5%
Other Punctuation
ValueCountFrequency (%)
, 3631
96.5%
. 102
 
2.7%
' 31
 
0.8%
Space Separator
ValueCountFrequency (%)
3712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41762
84.8%
Common 7500
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4086
 
9.8%
a 3371
 
8.1%
n 3261
 
7.8%
r 3107
 
7.4%
o 2900
 
6.9%
i 2762
 
6.6%
l 2308
 
5.5%
s 1802
 
4.3%
t 1496
 
3.6%
h 1177
 
2.8%
Other values (42) 15492
37.1%
Common
ValueCountFrequency (%)
3712
49.5%
, 3631
48.4%
. 102
 
1.4%
' 31
 
0.4%
- 24
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4086
 
8.3%
3712
 
7.5%
, 3631
 
7.4%
a 3371
 
6.8%
n 3261
 
6.6%
r 3107
 
6.3%
o 2900
 
5.9%
i 2762
 
5.6%
l 2308
 
4.7%
s 1802
 
3.7%
Other values (47) 18322
37.2%
Distinct3232
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:44.890697image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.554790749
Min length3

Characters and Unicode

Total characters34703
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2974 ?
Unique (%)81.9%

Sample

1st rowA. Abdelnaby
2nd rowZ. Abdul-Aziz
3rd rowK. Abdul-Jabbar
4th rowS. Abdur-Rahim
5th rowF. Able
ValueCountFrequency (%)
j 528
 
7.2%
d 342
 
4.7%
m 300
 
4.1%
b 256
 
3.5%
r 244
 
3.3%
c 234
 
3.2%
t 213
 
2.9%
a 210
 
2.9%
s 182
 
2.5%
k 153
 
2.1%
Other values (2295) 4665
63.7%
2023-07-13T22:06:45.201202image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3695
 
10.6%
. 3664
 
10.6%
e 2233
 
6.4%
n 1835
 
5.3%
a 1814
 
5.2%
r 1742
 
5.0%
o 1706
 
4.9%
i 1555
 
4.5%
l 1416
 
4.1%
s 1323
 
3.8%
Other values (46) 13720
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19797
57.0%
Uppercase Letter 7503
 
21.6%
Space Separator 3695
 
10.6%
Other Punctuation 3686
 
10.6%
Dash Punctuation 22
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2233
11.3%
n 1835
9.3%
a 1814
 
9.2%
r 1742
 
8.8%
o 1706
 
8.6%
i 1555
 
7.9%
l 1416
 
7.2%
s 1323
 
6.7%
t 978
 
4.9%
h 659
 
3.3%
Other values (16) 4536
22.9%
Uppercase Letter
ValueCountFrequency (%)
J 700
 
9.3%
M 667
 
8.9%
S 594
 
7.9%
B 575
 
7.7%
D 494
 
6.6%
R 491
 
6.5%
C 450
 
6.0%
W 439
 
5.9%
T 393
 
5.2%
A 325
 
4.3%
Other values (16) 2375
31.7%
Other Punctuation
ValueCountFrequency (%)
. 3664
99.4%
' 22
 
0.6%
Space Separator
ValueCountFrequency (%)
3695
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27300
78.7%
Common 7403
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2233
 
8.2%
n 1835
 
6.7%
a 1814
 
6.6%
r 1742
 
6.4%
o 1706
 
6.2%
i 1555
 
5.7%
l 1416
 
5.2%
s 1323
 
4.8%
t 978
 
3.6%
J 700
 
2.6%
Other values (42) 11998
43.9%
Common
ValueCountFrequency (%)
3695
49.9%
. 3664
49.5%
' 22
 
0.3%
- 22
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34703
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3695
 
10.6%
. 3664
 
10.6%
e 2233
 
6.4%
n 1835
 
5.3%
a 1814
 
5.2%
r 1742
 
5.0%
o 1706
 
4.9%
i 1555
 
4.5%
l 1416
 
4.1%
s 1323
 
3.8%
Other values (46) 13720
39.5%
Distinct3608
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:45.454898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.52946035
Min length7

Characters and Unicode

Total characters45507
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3585 ?
Unique (%)98.7%

Sample

1st rowalaa-abdelnaby
2nd rowzaid-abdul-aziz
3rd rowkareem-abdul-jabbar
4th rowshareef-abdur-rahim
5th rowforest-able
ValueCountFrequency (%)
charles-smith 3
 
0.1%
patrick-ewing 2
 
0.1%
george-johnson 2
 
0.1%
walker-russell 2
 
0.1%
charles-jones 2
 
0.1%
jack-turner 2
 
0.1%
michael-smith 2
 
0.1%
cedric-henderson 2
 
0.1%
brandon-williams 2
 
0.1%
greg-smith 2
 
0.1%
Other values (3598) 3611
99.4%
2023-07-13T22:06:45.787925image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4281
 
9.4%
- 3737
 
8.2%
a 3700
 
8.1%
r 3606
 
7.9%
n 3419
 
7.5%
o 3016
 
6.6%
i 2867
 
6.3%
l 2596
 
5.7%
s 2403
 
5.3%
t 1894
 
4.2%
Other values (18) 13988
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41768
91.8%
Dash Punctuation 3737
 
8.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4281
 
10.2%
a 3700
 
8.9%
r 3606
 
8.6%
n 3419
 
8.2%
o 3016
 
7.2%
i 2867
 
6.9%
l 2596
 
6.2%
s 2403
 
5.8%
t 1894
 
4.5%
m 1596
 
3.8%
Other values (16) 12390
29.7%
Dash Punctuation
ValueCountFrequency (%)
- 3737
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41768
91.8%
Common 3739
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4281
 
10.2%
a 3700
 
8.9%
r 3606
 
8.6%
n 3419
 
8.2%
o 3016
 
7.2%
i 2867
 
6.9%
l 2596
 
6.2%
s 2403
 
5.8%
t 1894
 
4.5%
m 1596
 
3.8%
Other values (16) 12390
29.7%
Common
ValueCountFrequency (%)
- 3737
99.9%
, 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45507
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4281
 
9.4%
- 3737
 
8.2%
a 3700
 
8.1%
r 3606
 
7.9%
n 3419
 
7.5%
o 3016
 
6.6%
i 2867
 
6.3%
l 2596
 
5.7%
s 2403
 
5.3%
t 1894
 
4.2%
Other values (18) 13988
30.7%
Distinct3412
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:46.046645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters69008
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3201 ?
Unique (%)88.1%

Sample

1st row1968-06-24 00:00:00
2nd row1946-04-07 00:00:00
3rd row1947-04-16 00:00:00
4th row1976-12-11 00:00:00
5th row1932-07-27 00:00:00
ValueCountFrequency (%)
00:00:00 3632
50.0%
1905-04-14 3
 
< 0.1%
1905-04-04 3
 
< 0.1%
1961-01-04 3
 
< 0.1%
1970-05-17 3
 
< 0.1%
1996-09-19 3
 
< 0.1%
1985-12-03 3
 
< 0.1%
1985-06-01 3
 
< 0.1%
1984-06-26 3
 
< 0.1%
1990-09-21 3
 
< 0.1%
Other values (3403) 3605
49.6%
2023-07-13T22:06:46.350484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26953
39.1%
- 7264
 
10.5%
: 7264
 
10.5%
1 7024
 
10.2%
9 5159
 
7.5%
3632
 
5.3%
2 2916
 
4.2%
8 1593
 
2.3%
6 1562
 
2.3%
7 1492
 
2.2%
Other values (3) 4149
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50848
73.7%
Dash Punctuation 7264
 
10.5%
Other Punctuation 7264
 
10.5%
Space Separator 3632
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26953
53.0%
1 7024
 
13.8%
9 5159
 
10.1%
2 2916
 
5.7%
8 1593
 
3.1%
6 1562
 
3.1%
7 1492
 
2.9%
5 1474
 
2.9%
3 1409
 
2.8%
4 1266
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 7264
100.0%
Other Punctuation
ValueCountFrequency (%)
: 7264
100.0%
Space Separator
ValueCountFrequency (%)
3632
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26953
39.1%
- 7264
 
10.5%
: 7264
 
10.5%
1 7024
 
10.2%
9 5159
 
7.5%
3632
 
5.3%
2 2916
 
4.2%
8 1593
 
2.3%
6 1562
 
2.3%
7 1492
 
2.2%
Other values (3) 4149
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26953
39.1%
- 7264
 
10.5%
: 7264
 
10.5%
1 7024
 
10.2%
9 5159
 
7.5%
3632
 
5.3%
2 2916
 
4.2%
8 1593
 
2.3%
6 1562
 
2.3%
7 1492
 
2.2%
Other values (3) 4149
 
6.0%

school
Text

Distinct599
Distinct (%)16.5%
Missing1
Missing (%)< 0.1%
Memory size28.5 KiB
2023-07-13T22:06:46.615473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length28
Mean length10.70228587
Min length0

Characters and Unicode

Total characters38860
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)8.2%

Sample

1st rowDuke
2nd rowIowa State
3rd rowUCLA
4th rowCalifornia
5th rowWestern Kentucky
ValueCountFrequency (%)
state 543
 
9.8%
carolina 126
 
2.3%
kentucky 123
 
2.2%
north 111
 
2.0%
st 104
 
1.9%
michigan 103
 
1.9%
arizona 81
 
1.5%
kansas 76
 
1.4%
virginia 70
 
1.3%
california 69
 
1.2%
Other values (638) 4120
74.6%
2023-07-13T22:06:46.942099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4008
 
10.3%
e 3192
 
8.2%
n 2853
 
7.3%
t 2780
 
7.2%
i 2672
 
6.9%
o 2603
 
6.7%
2228
 
5.7%
r 2001
 
5.1%
s 1733
 
4.5%
l 1504
 
3.9%
Other values (52) 13286
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29724
76.5%
Uppercase Letter 6261
 
16.1%
Space Separator 2228
 
5.7%
Other Punctuation 225
 
0.6%
Dash Punctuation 170
 
0.4%
Open Punctuation 125
 
0.3%
Close Punctuation 125
 
0.3%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4008
13.5%
e 3192
10.7%
n 2853
9.6%
t 2780
9.4%
i 2672
9.0%
o 2603
8.8%
r 2001
 
6.7%
s 1733
 
5.8%
l 1504
 
5.1%
u 978
 
3.3%
Other values (16) 5400
18.2%
Uppercase Letter
ValueCountFrequency (%)
S 1019
16.3%
C 602
 
9.6%
M 503
 
8.0%
A 398
 
6.4%
N 358
 
5.7%
L 329
 
5.3%
T 297
 
4.7%
P 239
 
3.8%
D 236
 
3.8%
W 234
 
3.7%
Other values (16) 2046
32.7%
Other Punctuation
ValueCountFrequency (%)
. 122
54.2%
' 72
32.0%
& 30
 
13.3%
, 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
2228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%
Open Punctuation
ValueCountFrequency (%)
( 125
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35985
92.6%
Common 2875
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4008
 
11.1%
e 3192
 
8.9%
n 2853
 
7.9%
t 2780
 
7.7%
i 2672
 
7.4%
o 2603
 
7.2%
r 2001
 
5.6%
s 1733
 
4.8%
l 1504
 
4.2%
S 1019
 
2.8%
Other values (42) 11620
32.3%
Common
ValueCountFrequency (%)
2228
77.5%
- 170
 
5.9%
( 125
 
4.3%
) 125
 
4.3%
. 122
 
4.2%
' 72
 
2.5%
& 30
 
1.0%
, 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4008
 
10.3%
e 3192
 
8.2%
n 2853
 
7.3%
t 2780
 
7.2%
i 2672
 
6.9%
o 2603
 
6.7%
2228
 
5.7%
r 2001
 
5.1%
s 1733
 
4.5%
l 1504
 
3.9%
Other values (52) 13286
34.2%
Distinct69
Distinct (%)1.9%
Missing1
Missing (%)< 0.1%
Memory size28.5 KiB
2023-07-13T22:06:47.080497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length22
Median length3
Mean length3.431561553
Min length3

Characters and Unicode

Total characters12460
Distinct characters45
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)0.8%

Sample

1st rowUSA
2nd rowUSA
3rd rowUSA
4th rowUSA
5th rowUSA
ValueCountFrequency (%)
usa 3274
89.2%
canada 35
 
1.0%
france 32
 
0.9%
serbia 21
 
0.6%
croatia 18
 
0.5%
australia 17
 
0.5%
brazil 14
 
0.4%
argentina 13
 
0.4%
turkey 11
 
0.3%
germany 11
 
0.3%
Other values (70) 223
 
6.1%
2023-07-13T22:06:47.281438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 3340
26.8%
A 3307
26.5%
U 3287
26.4%
a 462
 
3.7%
i 239
 
1.9%
n 238
 
1.9%
e 232
 
1.9%
r 198
 
1.6%
t 102
 
0.8%
o 99
 
0.8%
Other values (35) 956
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10217
82.0%
Lowercase Letter 2205
 
17.7%
Space Separator 38
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 462
21.0%
i 239
10.8%
n 238
10.8%
e 232
10.5%
r 198
9.0%
t 102
 
4.6%
o 99
 
4.5%
l 89
 
4.0%
u 81
 
3.7%
c 73
 
3.3%
Other values (13) 392
17.8%
Uppercase Letter
ValueCountFrequency (%)
S 3340
32.7%
A 3307
32.4%
U 3287
32.2%
C 68
 
0.7%
F 35
 
0.3%
G 29
 
0.3%
R 25
 
0.2%
B 22
 
0.2%
L 16
 
0.2%
T 15
 
0.1%
Other values (11) 73
 
0.7%
Space Separator
ValueCountFrequency (%)
38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12422
99.7%
Common 38
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 3340
26.9%
A 3307
26.6%
U 3287
26.5%
a 462
 
3.7%
i 239
 
1.9%
n 238
 
1.9%
e 232
 
1.9%
r 198
 
1.6%
t 102
 
0.8%
o 99
 
0.8%
Other values (34) 918
 
7.4%
Common
ValueCountFrequency (%)
38
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 3340
26.8%
A 3307
26.5%
U 3287
26.4%
a 462
 
3.7%
i 239
 
1.9%
n 238
 
1.9%
e 232
 
1.9%
r 198
 
1.6%
t 102
 
0.8%
o 99
 
0.8%
Other values (35) 956
 
7.7%
Distinct771
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:47.546546image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length39
Median length31
Mean length15.10737885
Min length7

Characters and Unicode

Total characters54870
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique472 ?
Unique (%)13.0%

Sample

1st rowDuke/USA
2nd rowIowa State/USA
3rd rowUCLA/USA
4th rowCalifornia/USA
5th rowWestern Kentucky/USA
ValueCountFrequency (%)
state/usa 522
 
9.3%
north 111
 
2.0%
kentucky/usa 109
 
1.9%
st 105
 
1.9%
carolina/usa 83
 
1.5%
ucla/usa 61
 
1.1%
tech/usa 61
 
1.1%
duke/usa 60
 
1.1%
michigan/usa 58
 
1.0%
kansas/usa 54
 
1.0%
Other values (896) 4368
78.1%
2023-07-13T22:06:47.876158image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4497
 
8.2%
S 4364
 
8.0%
A 3716
 
6.8%
/ 3631
 
6.6%
U 3460
 
6.3%
e 3445
 
6.3%
n 3110
 
5.7%
i 2932
 
5.3%
t 2893
 
5.3%
o 2710
 
4.9%
Other values (52) 20112
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32101
58.5%
Uppercase Letter 16524
30.1%
Other Punctuation 3852
 
7.0%
Space Separator 1960
 
3.6%
Dash Punctuation 175
 
0.3%
Close Punctuation 128
 
0.2%
Open Punctuation 128
 
0.2%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4497
14.0%
e 3445
10.7%
n 3110
9.7%
i 2932
9.1%
t 2893
9.0%
o 2710
8.4%
r 2206
 
6.9%
s 1790
 
5.6%
l 1604
 
5.0%
u 1063
 
3.3%
Other values (16) 5851
18.2%
Uppercase Letter
ValueCountFrequency (%)
S 4364
26.4%
A 3716
22.5%
U 3460
20.9%
C 674
 
4.1%
M 518
 
3.1%
N 370
 
2.2%
L 341
 
2.1%
T 312
 
1.9%
B 260
 
1.6%
P 250
 
1.5%
Other values (16) 2259
13.7%
Other Punctuation
ValueCountFrequency (%)
/ 3631
94.3%
. 119
 
3.1%
' 72
 
1.9%
& 30
 
0.8%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
1960
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 48625
88.6%
Common 6245
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4497
 
9.2%
S 4364
 
9.0%
A 3716
 
7.6%
U 3460
 
7.1%
e 3445
 
7.1%
n 3110
 
6.4%
i 2932
 
6.0%
t 2893
 
5.9%
o 2710
 
5.6%
r 2206
 
4.5%
Other values (42) 15292
31.4%
Common
ValueCountFrequency (%)
/ 3631
58.1%
1960
31.4%
- 175
 
2.8%
) 128
 
2.0%
( 128
 
2.0%
. 119
 
1.9%
' 72
 
1.2%
& 30
 
0.5%
8 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54870
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4497
 
8.2%
S 4364
 
8.0%
A 3716
 
6.8%
/ 3631
 
6.6%
U 3460
 
6.3%
e 3445
 
6.3%
n 3110
 
5.7%
i 2932
 
5.3%
t 2893
 
5.3%
o 2710
 
4.9%
Other values (52) 20112
36.7%

height
Text

Distinct27
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:48.011217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.084526432
Min length0

Characters and Unicode

Total characters11203
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row6-10
2nd row6-9
3rd row7-2
4th row6-9
5th row6-3
ValueCountFrequency (%)
6-5 352
9.9%
6-7 340
9.6%
6-8 326
9.2%
6-9 319
9.0%
6-6 317
8.9%
6-3 301
8.5%
6-4 292
8.2%
6-10 269
7.6%
6-2 265
7.4%
6-11 178
 
5.0%
Other values (16) 599
16.8%
2023-07-13T22:06:48.187419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3558
31.8%
6 3557
31.8%
1 968
 
8.6%
7 566
 
5.1%
0 543
 
4.8%
5 457
 
4.1%
9 330
 
2.9%
8 328
 
2.9%
3 312
 
2.8%
4 295
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7645
68.2%
Dash Punctuation 3558
31.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 3557
46.5%
1 968
 
12.7%
7 566
 
7.4%
0 543
 
7.1%
5 457
 
6.0%
9 330
 
4.3%
8 328
 
4.3%
3 312
 
4.1%
4 295
 
3.9%
2 289
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 3558
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11203
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 3558
31.8%
6 3557
31.8%
1 968
 
8.6%
7 566
 
5.1%
0 543
 
4.8%
5 457
 
4.1%
9 330
 
2.9%
8 328
 
2.9%
3 312
 
2.8%
4 295
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 3558
31.8%
6 3557
31.8%
1 968
 
8.6%
7 566
 
5.1%
0 543
 
4.8%
5 457
 
4.1%
9 330
 
2.9%
8 328
 
2.9%
3 312
 
2.8%
4 295
 
2.6%

weight
Text

Distinct135
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:48.382381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.936398678
Min length0

Characters and Unicode

Total characters10665
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)0.7%

Sample

1st row240
2nd row235
3rd row225
4th row245
5th row180
ValueCountFrequency (%)
190 231
 
6.5%
210 225
 
6.3%
185 214
 
6.0%
200 193
 
5.4%
220 193
 
5.4%
195 191
 
5.4%
215 180
 
5.1%
205 166
 
4.7%
225 163
 
4.6%
180 148
 
4.2%
Other values (124) 1651
46.4%
2023-07-13T22:06:48.633193image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2816
26.4%
0 2010
18.8%
1 1803
16.9%
5 1582
14.8%
8 572
 
5.4%
9 571
 
5.4%
3 387
 
3.6%
7 355
 
3.3%
4 335
 
3.1%
6 234
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10665
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2816
26.4%
0 2010
18.8%
1 1803
16.9%
5 1582
14.8%
8 572
 
5.4%
9 571
 
5.4%
3 387
 
3.6%
7 355
 
3.3%
4 335
 
3.1%
6 234
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 10665
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2816
26.4%
0 2010
18.8%
1 1803
16.9%
5 1582
14.8%
8 572
 
5.4%
9 571
 
5.4%
3 387
 
3.6%
7 355
 
3.3%
4 335
 
3.1%
6 234
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10665
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2816
26.4%
0 2010
18.8%
1 1803
16.9%
5 1582
14.8%
8 572
 
5.4%
9 571
 
5.4%
3 387
 
3.6%
7 355
 
3.3%
4 335
 
3.1%
6 234
 
2.2%

season_exp
Real number (ℝ)

Distinct24
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.237059471
Minimum0
Maximum23
Zeros5
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:48.698349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q38
95-th percentile14
Maximum23
Range23
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.49317521
Coefficient of variation (CV)0.8579576448
Kurtosis0.2935445846
Mean5.237059471
Median Absolute Deviation (MAD)2
Skewness1.083287396
Sum19021
Variance20.18862346
MonotonicityNot monotonic
2023-07-13T22:06:48.745447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 806
22.2%
2 623
17.2%
3 400
11.0%
4 276
 
7.6%
5 219
 
6.0%
6 163
 
4.5%
10 156
 
4.3%
7 151
 
4.2%
9 134
 
3.7%
11 127
 
3.5%
Other values (14) 577
15.9%
ValueCountFrequency (%)
0 5
 
0.1%
1 806
22.2%
2 623
17.2%
3 400
11.0%
4 276
 
7.6%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 3
 
0.1%
21 1
 
< 0.1%
20 7
0.2%
19 14
0.4%

jersey
Text

Distinct104
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:48.916177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length7
Median length2
Mean length1.370319383
Min length0

Characters and Unicode

Total characters4977
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)1.1%

Sample

1st row30
2nd row54
3rd row33
4th row3
5th row6
ValueCountFrequency (%)
12 108
 
3.9%
20 101
 
3.6%
5 97
 
3.5%
15 94
 
3.4%
10 93
 
3.3%
11 93
 
3.3%
4 90
 
3.2%
3 90
 
3.2%
21 86
 
3.1%
22 80
 
2.9%
Other values (90) 1871
66.7%
2023-07-13T22:06:49.343473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1054
21.2%
2 919
18.5%
3 728
14.6%
4 682
13.7%
5 559
11.2%
0 430
8.6%
7 176
 
3.5%
6 139
 
2.8%
8 139
 
2.8%
9 120
 
2.4%
Other values (2) 31
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4946
99.4%
Dash Punctuation 24
 
0.5%
Space Separator 7
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1054
21.3%
2 919
18.6%
3 728
14.7%
4 682
13.8%
5 559
11.3%
0 430
8.7%
7 176
 
3.6%
6 139
 
2.8%
8 139
 
2.8%
9 120
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1054
21.2%
2 919
18.5%
3 728
14.6%
4 682
13.7%
5 559
11.2%
0 430
8.6%
7 176
 
3.5%
6 139
 
2.8%
8 139
 
2.8%
9 120
 
2.4%
Other values (2) 31
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1054
21.2%
2 919
18.5%
3 728
14.6%
4 682
13.7%
5 559
11.2%
0 430
8.6%
7 176
 
3.5%
6 139
 
2.8%
8 139
 
2.8%
9 120
 
2.4%
Other values (2) 31
 
0.6%
Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:49.468210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.654185022
Min length0

Characters and Unicode

Total characters24168
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowForward
2nd rowCenter
3rd rowCenter
4th rowForward
5th rowGuard
ValueCountFrequency (%)
guard 1416
39.5%
forward 1306
36.4%
center 497
 
13.9%
guard-forward 134
 
3.7%
forward-center 112
 
3.1%
center-forward 68
 
1.9%
forward-guard 54
 
1.5%
2023-07-13T22:06:49.645743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 5629
23.3%
a 3278
13.6%
d 3278
13.6%
F 1674
 
6.9%
o 1674
 
6.9%
w 1674
 
6.9%
G 1604
 
6.6%
u 1604
 
6.6%
e 1354
 
5.6%
C 677
 
2.8%
Other values (3) 1722
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19845
82.1%
Uppercase Letter 3955
 
16.4%
Dash Punctuation 368
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 5629
28.4%
a 3278
16.5%
d 3278
16.5%
o 1674
 
8.4%
w 1674
 
8.4%
u 1604
 
8.1%
e 1354
 
6.8%
n 677
 
3.4%
t 677
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
F 1674
42.3%
G 1604
40.6%
C 677
17.1%
Dash Punctuation
ValueCountFrequency (%)
- 368
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23800
98.5%
Common 368
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 5629
23.7%
a 3278
13.8%
d 3278
13.8%
F 1674
 
7.0%
o 1674
 
7.0%
w 1674
 
7.0%
G 1604
 
6.7%
u 1604
 
6.7%
e 1354
 
5.7%
C 677
 
2.8%
Other values (2) 1354
 
5.7%
Common
ValueCountFrequency (%)
- 368
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 5629
23.3%
a 3278
13.6%
d 3278
13.6%
F 1674
 
6.9%
o 1674
 
6.9%
w 1674
 
6.9%
G 1604
 
6.6%
u 1604
 
6.6%
e 1354
 
5.6%
C 677
 
2.8%
Other values (3) 1722
 
7.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:49.748235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.783590308
Min length6

Characters and Unicode

Total characters28270
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowInactive
2nd rowInactive
3rd rowInactive
4th rowInactive
5th rowInactive
ValueCountFrequency (%)
inactive 3239
89.2%
active 393
 
10.8%
2023-07-13T22:06:49.912246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 3632
12.8%
t 3632
12.8%
i 3632
12.8%
v 3632
12.8%
e 3632
12.8%
I 3239
11.5%
n 3239
11.5%
a 3239
11.5%
A 393
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24638
87.2%
Uppercase Letter 3632
 
12.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 3632
14.7%
t 3632
14.7%
i 3632
14.7%
v 3632
14.7%
e 3632
14.7%
n 3239
13.1%
a 3239
13.1%
Uppercase Letter
ValueCountFrequency (%)
I 3239
89.2%
A 393
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 28270
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 3632
12.8%
t 3632
12.8%
i 3632
12.8%
v 3632
12.8%
e 3632
12.8%
I 3239
11.5%
n 3239
11.5%
a 3239
11.5%
A 393
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 3632
12.8%
t 3632
12.8%
i 3632
12.8%
v 3632
12.8%
e 3632
12.8%
I 3239
11.5%
n 3239
11.5%
a 3239
11.5%
A 393
 
1.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:50.122569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3632
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 3632
100.0%
2023-07-13T22:06:50.246968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 3632
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3632
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 3632
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3632
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3632
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3632
100.0%

team_id
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1345872565
Minimum0
Maximum1610612766
Zeros597
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:50.312206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11610612737
median1610612746
Q31610612757
95-th percentile1610612765
Maximum1610612766
Range1610612766
Interquartile range (IQR)20

Descriptive statistics

Standard deviation596996181.8
Coefficient of variation (CV)0.4435755639
Kurtosis1.283875497
Mean1345872565
Median Absolute Deviation (MAD)9
Skewness-1.811951661
Sum4.888209155 × 1012
Variance3.564044411 × 1017
MonotonicityNot monotonic
2023-07-13T22:06:50.372989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 597
 
16.4%
1610612744 172
 
4.7%
1610612737 162
 
4.5%
1610612752 155
 
4.3%
1610612765 153
 
4.2%
1610612758 141
 
3.9%
1610612738 133
 
3.7%
1610612747 129
 
3.6%
1610612755 123
 
3.4%
1610612764 123
 
3.4%
Other values (36) 1744
48.0%
ValueCountFrequency (%)
0 597
16.4%
1610610023 6
 
0.2%
1610610024 39
 
1.1%
1610610025 19
 
0.5%
1610610026 6
 
0.2%
ValueCountFrequency (%)
1610612766 54
 
1.5%
1610612765 153
4.2%
1610612764 123
3.4%
1610612763 52
 
1.4%
1610612762 79
2.2%
Distinct51
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:50.556558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.662995595
Min length0

Characters and Unicode

Total characters20568
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTrail Blazers
2nd rowRockets
3rd rowLakers
4th rowGrizzlies
5th rowNationals
ValueCountFrequency (%)
warriors 172
 
5.5%
hawks 161
 
5.1%
knicks 155
 
4.9%
pistons 153
 
4.9%
celtics 133
 
4.2%
lakers 129
 
4.1%
bullets 108
 
3.4%
trail 101
 
3.2%
blazers 101
 
3.2%
76ers 98
 
3.1%
Other values (41) 1825
58.2%
2023-07-13T22:06:50.795600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 2994
14.6%
r 1775
 
8.6%
e 1664
 
8.1%
a 1513
 
7.4%
i 1457
 
7.1%
l 1200
 
5.8%
t 905
 
4.4%
c 789
 
3.8%
o 779
 
3.8%
n 741
 
3.6%
Other values (33) 6751
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17166
83.5%
Uppercase Letter 3105
 
15.1%
Decimal Number 196
 
1.0%
Space Separator 101
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2994
17.4%
r 1775
10.3%
e 1664
9.7%
a 1513
8.8%
i 1457
8.5%
l 1200
 
7.0%
t 905
 
5.3%
c 789
 
4.6%
o 779
 
4.5%
n 741
 
4.3%
Other values (12) 3349
19.5%
Uppercase Letter
ValueCountFrequency (%)
B 435
14.0%
S 342
11.0%
C 326
10.5%
H 268
8.6%
P 265
8.5%
K 244
7.9%
W 217
7.0%
R 204
6.6%
N 202
6.5%
T 172
 
5.5%
Other values (8) 430
13.8%
Decimal Number
ValueCountFrequency (%)
6 98
50.0%
7 98
50.0%
Space Separator
ValueCountFrequency (%)
101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20271
98.6%
Common 297
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2994
14.8%
r 1775
 
8.8%
e 1664
 
8.2%
a 1513
 
7.5%
i 1457
 
7.2%
l 1200
 
5.9%
t 905
 
4.5%
c 789
 
3.9%
o 779
 
3.8%
n 741
 
3.7%
Other values (30) 6454
31.8%
Common
ValueCountFrequency (%)
101
34.0%
6 98
33.0%
7 98
33.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2994
14.6%
r 1775
 
8.6%
e 1664
 
8.1%
a 1513
 
7.4%
i 1457
 
7.1%
l 1200
 
5.8%
t 905
 
4.4%
c 789
 
3.8%
o 779
 
3.8%
n 741
 
3.6%
Other values (33) 6751
32.8%
Distinct70
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:50.960911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.503854626
Min length0

Characters and Unicode

Total characters9094
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPOR
2nd rowHOU
3rd rowLAL
4th rowVAN
5th rowPHI
ValueCountFrequency (%)
nyk 155
 
5.1%
bos 133
 
4.4%
det 129
 
4.3%
phi 123
 
4.1%
atl 114
 
3.8%
was 106
 
3.5%
por 101
 
3.3%
lal 99
 
3.3%
phx 96
 
3.2%
chi 94
 
3.1%
Other values (59) 1885
62.1%
2023-07-13T22:06:51.183291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 902
 
9.9%
L 784
 
8.6%
S 717
 
7.9%
N 640
 
7.0%
O 593
 
6.5%
H 590
 
6.5%
I 544
 
6.0%
C 542
 
6.0%
T 466
 
5.1%
E 441
 
4.8%
Other values (15) 2875
31.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9094
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 902
 
9.9%
L 784
 
8.6%
S 717
 
7.9%
N 640
 
7.0%
O 593
 
6.5%
H 590
 
6.5%
I 544
 
6.0%
C 542
 
6.0%
T 466
 
5.1%
E 441
 
4.8%
Other values (15) 2875
31.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 9094
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 902
 
9.9%
L 784
 
8.6%
S 717
 
7.9%
N 640
 
7.0%
O 593
 
6.5%
H 590
 
6.5%
I 544
 
6.0%
C 542
 
6.0%
T 466
 
5.1%
E 441
 
4.8%
Other values (15) 2875
31.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9094
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 902
 
9.9%
L 784
 
8.6%
S 717
 
7.9%
N 640
 
7.0%
O 593
 
6.5%
H 590
 
6.5%
I 544
 
6.0%
C 542
 
6.0%
T 466
 
5.1%
E 441
 
4.8%
Other values (15) 2875
31.6%
Distinct44
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:51.358443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length8
Mean length5.412444934
Min length0

Characters and Unicode

Total characters19658
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowblazers
2nd rowrockets
3rd rowlakers
4th rowgrizzlies
5th rowsixers
ValueCountFrequency (%)
warriors 172
 
5.7%
hawks 171
 
5.6%
knicks 155
 
5.1%
pistons 153
 
5.0%
kings 141
 
4.6%
celtics 133
 
4.4%
lakers 129
 
4.3%
sixers 123
 
4.1%
wizards 123
 
4.1%
clippers 107
 
3.5%
Other values (33) 1628
53.6%
2023-07-13T22:06:51.588826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 3258
16.6%
r 1923
 
9.8%
e 1625
 
8.3%
i 1555
 
7.9%
a 1354
 
6.9%
c 1046
 
5.3%
l 1030
 
5.2%
k 1019
 
5.2%
n 959
 
4.9%
t 938
 
4.8%
Other values (15) 4951
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19658
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 3258
16.6%
r 1923
 
9.8%
e 1625
 
8.3%
i 1555
 
7.9%
a 1354
 
6.9%
c 1046
 
5.3%
l 1030
 
5.2%
k 1019
 
5.2%
n 959
 
4.9%
t 938
 
4.8%
Other values (15) 4951
25.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 19658
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 3258
16.6%
r 1923
 
9.8%
e 1625
 
8.3%
i 1555
 
7.9%
a 1354
 
6.9%
c 1046
 
5.3%
l 1030
 
5.2%
k 1019
 
5.2%
n 959
 
4.9%
t 938
 
4.8%
Other values (15) 4951
25.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 3258
16.6%
r 1923
 
9.8%
e 1625
 
8.3%
i 1555
 
7.9%
a 1354
 
6.9%
c 1046
 
5.3%
l 1030
 
5.2%
k 1019
 
5.2%
n 959
 
4.9%
t 938
 
4.8%
Other values (15) 4951
25.2%
Distinct55
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:51.771786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length13
Mean length7.13160793
Min length0

Characters and Unicode

Total characters25902
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPortland
2nd rowHouston
3rd rowLos Angeles
4th rowVancouver
5th rowSyracuse
ValueCountFrequency (%)
new 250
 
6.6%
york 157
 
4.1%
los 151
 
4.0%
angeles 151
 
4.0%
philadelphia 147
 
3.9%
detroit 137
 
3.6%
boston 133
 
3.5%
chicago 122
 
3.2%
san 115
 
3.0%
atlanta 114
 
3.0%
Other values (52) 2327
61.2%
2023-07-13T22:06:52.008931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2487
 
9.6%
a 2485
 
9.6%
o 2309
 
8.9%
n 2282
 
8.8%
t 1961
 
7.6%
i 1662
 
6.4%
l 1652
 
6.4%
s 1125
 
4.3%
r 1017
 
3.9%
h 866
 
3.3%
Other values (40) 8056
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21205
81.9%
Uppercase Letter 3847
 
14.9%
Space Separator 769
 
3.0%
Other Punctuation 65
 
0.3%
Dash Punctuation 16
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2487
11.7%
a 2485
11.7%
o 2309
10.9%
n 2282
10.8%
t 1961
9.2%
i 1662
7.8%
l 1652
7.8%
s 1125
 
5.3%
r 1017
 
4.8%
h 866
 
4.1%
Other values (13) 3359
15.8%
Uppercase Letter
ValueCountFrequency (%)
S 418
10.9%
C 381
9.9%
P 372
9.7%
A 369
9.6%
D 328
 
8.5%
M 260
 
6.8%
N 250
 
6.5%
B 233
 
6.1%
L 209
 
5.4%
Y 157
 
4.1%
Other values (13) 870
22.6%
Other Punctuation
ValueCountFrequency (%)
. 60
92.3%
/ 5
 
7.7%
Space Separator
ValueCountFrequency (%)
769
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25052
96.7%
Common 850
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2487
 
9.9%
a 2485
 
9.9%
o 2309
 
9.2%
n 2282
 
9.1%
t 1961
 
7.8%
i 1662
 
6.6%
l 1652
 
6.6%
s 1125
 
4.5%
r 1017
 
4.1%
h 866
 
3.5%
Other values (36) 7206
28.8%
Common
ValueCountFrequency (%)
769
90.5%
. 60
 
7.1%
- 16
 
1.9%
/ 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2487
 
9.6%
a 2485
 
9.6%
o 2309
 
8.9%
n 2282
 
8.8%
t 1961
 
7.6%
i 1662
 
6.4%
l 1652
 
6.4%
s 1125
 
4.3%
r 1017
 
3.9%
h 866
 
3.3%
Other values (40) 8056
31.1%
Distinct3621
Distinct (%)99.7%
Missing1
Missing (%)< 0.1%
Memory size28.5 KiB
2023-07-13T22:06:52.244437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length33
Median length26
Mean length16.12228036
Min length7

Characters and Unicode

Total characters58540
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3611 ?
Unique (%)99.4%

Sample

1st rowHISTADD_alaa_abdelnaby
2nd rowHISTADD_zaid_abdul-aziz
3rd rowHISTADD_kareem_abdul-jabbar
4th rowshareef_abdur-rahim
5th rowHISTADD_frosty_able
ValueCountFrequency (%)
iii 3
 
0.1%
marcus_williams 2
 
0.1%
steven_smith 2
 
0.1%
glenn_robinson 2
 
0.1%
glen_rice 2
 
0.1%
chris_johnson 2
 
0.1%
jabari_smith 2
 
0.1%
jr 2
 
0.1%
charles_smith 2
 
0.1%
chris_wright 2
 
0.1%
Other values (3619) 3622
99.4%
2023-07-13T22:06:52.577775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 5320
 
9.1%
e 4281
 
7.3%
a 3655
 
6.2%
r 3568
 
6.1%
n 3392
 
5.8%
D 3222
 
5.5%
o 3007
 
5.1%
i 2859
 
4.9%
l 2564
 
4.4%
s 2427
 
4.1%
Other values (28) 24245
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41851
71.5%
Uppercase Letter 11277
 
19.3%
Connector Punctuation 5320
 
9.1%
Other Punctuation 55
 
0.1%
Dash Punctuation 25
 
< 0.1%
Space Separator 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4281
 
10.2%
a 3655
 
8.7%
r 3568
 
8.5%
n 3392
 
8.1%
o 3007
 
7.2%
i 2859
 
6.8%
l 2564
 
6.1%
s 2427
 
5.8%
t 1922
 
4.6%
m 1609
 
3.8%
Other values (16) 12567
30.0%
Uppercase Letter
ValueCountFrequency (%)
D 3222
28.6%
I 1611
14.3%
A 1611
14.3%
T 1611
14.3%
S 1611
14.3%
H 1611
14.3%
Other Punctuation
ValueCountFrequency (%)
. 31
56.4%
' 23
41.8%
; 1
 
1.8%
Connector Punctuation
ValueCountFrequency (%)
_ 5320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 53128
90.8%
Common 5412
 
9.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4281
 
8.1%
a 3655
 
6.9%
r 3568
 
6.7%
n 3392
 
6.4%
D 3222
 
6.1%
o 3007
 
5.7%
i 2859
 
5.4%
l 2564
 
4.8%
s 2427
 
4.6%
t 1922
 
3.6%
Other values (22) 22231
41.8%
Common
ValueCountFrequency (%)
_ 5320
98.3%
. 31
 
0.6%
- 25
 
0.5%
' 23
 
0.4%
12
 
0.2%
; 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 5320
 
9.1%
e 4281
 
7.3%
a 3655
 
6.2%
r 3568
 
6.1%
n 3392
 
5.8%
D 3222
 
5.5%
o 3007
 
5.1%
i 2859
 
4.9%
l 2564
 
4.4%
s 2427
 
4.1%
Other values (28) 24245
41.4%

from_year
Real number (ℝ)

Distinct77
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1989.465859
Minimum1946
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:52.654443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1946
5-th percentile1948
Q11974
median1992
Q32010
95-th percentile2020
Maximum2022
Range76
Interquartile range (IQR)36

Descriptive statistics

Standard deviation22.87569999
Coefficient of variation (CV)0.01149841294
Kurtosis-0.9622384504
Mean1989.465859
Median Absolute Deviation (MAD)18
Skewness-0.3765895145
Sum7225740
Variance523.2976498
MonotonicityNot monotonic
2023-07-13T22:06:52.724543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1946 124
 
3.4%
2021 107
 
2.9%
2019 91
 
2.5%
1949 90
 
2.5%
2017 89
 
2.5%
1976 85
 
2.3%
2020 82
 
2.3%
2018 81
 
2.2%
1948 71
 
2.0%
2022 67
 
1.8%
Other values (67) 2745
75.6%
ValueCountFrequency (%)
1946 124
3.4%
1947 30
 
0.8%
1948 71
2.0%
1949 90
2.5%
1950 24
 
0.7%
ValueCountFrequency (%)
2022 67
1.8%
2021 107
2.9%
2020 82
2.3%
2019 91
2.5%
2018 81
2.2%

to_year
Real number (ℝ)

Distinct78
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1993.945485
Minimum1946
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:52.792215image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1946
5-th percentile1949
Q11977
median1998
Q32016
95-th percentile2023
Maximum2023
Range77
Interquartile range (IQR)39

Descriptive statistics

Standard deviation23.63172884
Coefficient of variation (CV)0.0118517427
Kurtosis-0.8764862158
Mean1993.945485
Median Absolute Deviation (MAD)19
Skewness-0.5181525059
Sum7242010
Variance558.4586081
MonotonicityNot monotonic
2023-07-13T22:06:52.851849image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2023 393
 
10.8%
2021 130
 
3.6%
2017 89
 
2.5%
2018 82
 
2.3%
1949 81
 
2.2%
2016 79
 
2.2%
2002 71
 
2.0%
1946 64
 
1.8%
2005 60
 
1.7%
2004 59
 
1.6%
Other values (68) 2524
69.5%
ValueCountFrequency (%)
1946 64
1.8%
1947 22
 
0.6%
1948 55
1.5%
1949 81
2.2%
1950 38
1.0%
ValueCountFrequency (%)
2023 393
10.8%
2022 37
 
1.0%
2021 130
 
3.6%
2020 54
 
1.5%
2019 58
 
1.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:52.896895image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3632
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 2672
73.6%
y 960
 
26.4%
2023-07-13T22:06:52.989995image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 2672
73.6%
Y 960
 
26.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3632
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2672
73.6%
Y 960
 
26.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 3632
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2672
73.6%
Y 960
 
26.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2672
73.6%
Y 960
 
26.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:53.035214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3632
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 3611
99.4%
n 21
 
0.6%
2023-07-13T22:06:53.135877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 3611
99.4%
N 21
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3632
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 3611
99.4%
N 21
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 3632
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 3611
99.4%
N 21
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 3611
99.4%
N 21
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:53.181198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3632
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 3619
99.6%
n 13
 
0.4%
2023-07-13T22:06:53.273979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 3619
99.6%
N 13
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3632
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 3619
99.6%
N 13
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 3632
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 3619
99.6%
N 13
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 3619
99.6%
N 13
 
0.4%
Distinct77
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:53.463176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length4
Mean length5.281662996
Min length4

Characters and Unicode

Total characters19183
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1990
2nd row1968
3rd row1969
4th row1996
5th row1956
ValueCountFrequency (%)
undrafted 931
25.6%
2018 54
 
1.5%
1982 54
 
1.5%
1978 53
 
1.5%
1986 53
 
1.5%
2020 52
 
1.4%
2019 51
 
1.4%
2017 49
 
1.3%
1977 49
 
1.3%
1980 48
 
1.3%
Other values (67) 2238
61.6%
2023-07-13T22:06:53.702785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2493
13.0%
9 2395
12.5%
d 1862
 
9.7%
0 1605
 
8.4%
2 1388
 
7.2%
e 931
 
4.9%
n 931
 
4.9%
U 931
 
4.9%
t 931
 
4.9%
f 931
 
4.9%
Other values (8) 4785
24.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10804
56.3%
Lowercase Letter 7448
38.8%
Uppercase Letter 931
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2493
23.1%
9 2395
22.2%
0 1605
14.9%
2 1388
12.8%
8 772
 
7.1%
7 696
 
6.4%
6 496
 
4.6%
5 421
 
3.9%
4 321
 
3.0%
3 217
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
d 1862
25.0%
e 931
12.5%
n 931
12.5%
t 931
12.5%
f 931
12.5%
a 931
12.5%
r 931
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 931
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10804
56.3%
Latin 8379
43.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2493
23.1%
9 2395
22.2%
0 1605
14.9%
2 1388
12.8%
8 772
 
7.1%
7 696
 
6.4%
6 496
 
4.6%
5 421
 
3.9%
4 321
 
3.0%
3 217
 
2.0%
Latin
ValueCountFrequency (%)
d 1862
22.2%
e 931
11.1%
n 931
11.1%
U 931
11.1%
t 931
11.1%
f 931
11.1%
a 931
11.1%
r 931
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19183
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2493
13.0%
9 2395
12.5%
d 1862
 
9.7%
0 1605
 
8.4%
2 1388
 
7.2%
e 931
 
4.9%
n 931
 
4.9%
U 931
 
4.9%
t 931
 
4.9%
f 931
 
4.9%
Other values (8) 4785
24.9%

draft_round
Text

MISSING 

Distinct18
Distinct (%)0.5%
Missing146
Missing (%)4.0%
Memory size28.5 KiB
2023-07-13T22:06:53.824714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length1
Mean length3.146012622
Min length1

Characters and Unicode

Total characters10967
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th rowUndrafted
ValueCountFrequency (%)
1 1193
34.2%
undrafted 931
26.7%
2 869
24.9%
3 187
 
5.4%
4 100
 
2.9%
5 60
 
1.7%
6 37
 
1.1%
7 35
 
1.0%
8 24
 
0.7%
10 12
 
0.3%
Other values (8) 38
 
1.1%
2023-07-13T22:06:53.996005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1862
17.0%
1 1235
11.3%
U 931
8.5%
n 931
8.5%
r 931
8.5%
a 931
8.5%
f 931
8.5%
t 931
8.5%
e 931
8.5%
2 876
8.0%
Other values (8) 477
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7448
67.9%
Decimal Number 2588
 
23.6%
Uppercase Letter 931
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1235
47.7%
2 876
33.8%
3 187
 
7.2%
4 100
 
3.9%
5 61
 
2.4%
6 37
 
1.4%
7 37
 
1.4%
8 24
 
0.9%
0 22
 
0.9%
9 9
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
d 1862
25.0%
n 931
12.5%
r 931
12.5%
a 931
12.5%
f 931
12.5%
t 931
12.5%
e 931
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 931
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8379
76.4%
Common 2588
 
23.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1235
47.7%
2 876
33.8%
3 187
 
7.2%
4 100
 
3.9%
5 61
 
2.4%
6 37
 
1.4%
7 37
 
1.4%
8 24
 
0.9%
0 22
 
0.9%
9 9
 
0.3%
Latin
ValueCountFrequency (%)
d 1862
22.2%
U 931
11.1%
n 931
11.1%
r 931
11.1%
a 931
11.1%
f 931
11.1%
t 931
11.1%
e 931
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1862
17.0%
1 1235
11.3%
U 931
8.5%
n 931
8.5%
r 931
8.5%
a 931
8.5%
f 931
8.5%
t 931
8.5%
e 931
8.5%
2 876
8.0%
Other values (8) 477
 
4.3%

draft_number
Text

MISSING 

Distinct155
Distinct (%)4.5%
Missing198
Missing (%)5.5%
Memory size28.5 KiB
2023-07-13T22:06:54.692154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length2
Mean length3.774315667
Min length1

Characters and Unicode

Total characters12961
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)1.1%

Sample

1st row25
2nd row5
3rd row1
4th row3
5th rowUndrafted
ValueCountFrequency (%)
undrafted 931
27.1%
4 67
 
2.0%
6 59
 
1.7%
1 58
 
1.7%
9 58
 
1.7%
2 57
 
1.7%
5 57
 
1.7%
18 53
 
1.5%
10 53
 
1.5%
7 52
 
1.5%
Other values (145) 1989
57.9%
2023-07-13T22:06:54.938469image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1862
14.4%
U 931
 
7.2%
r 931
 
7.2%
a 931
 
7.2%
f 931
 
7.2%
t 931
 
7.2%
e 931
 
7.2%
n 931
 
7.2%
1 852
 
6.6%
2 696
 
5.4%
Other values (8) 3034
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7448
57.5%
Decimal Number 4582
35.4%
Uppercase Letter 931
 
7.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 852
18.6%
2 696
15.2%
3 623
13.6%
4 545
11.9%
5 473
10.3%
6 338
 
7.4%
8 277
 
6.0%
7 273
 
6.0%
0 260
 
5.7%
9 245
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
d 1862
25.0%
r 931
12.5%
a 931
12.5%
f 931
12.5%
t 931
12.5%
e 931
12.5%
n 931
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 931
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8379
64.6%
Common 4582
35.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 852
18.6%
2 696
15.2%
3 623
13.6%
4 545
11.9%
5 473
10.3%
6 338
 
7.4%
8 277
 
6.0%
7 273
 
6.0%
0 260
 
5.7%
9 245
 
5.3%
Latin
ValueCountFrequency (%)
d 1862
22.2%
U 931
11.1%
r 931
11.1%
a 931
11.1%
f 931
11.1%
t 931
11.1%
e 931
11.1%
n 931
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12961
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1862
14.4%
U 931
 
7.2%
r 931
 
7.2%
a 931
 
7.2%
f 931
 
7.2%
t 931
 
7.2%
e 931
 
7.2%
n 931
 
7.2%
1 852
 
6.6%
2 696
 
5.4%
Other values (8) 3034
23.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-07-13T22:06:54.991179image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3632
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowY
4th rowN
5th rowN
ValueCountFrequency (%)
n 3573
98.4%
y 59
 
1.6%
2023-07-13T22:06:55.085170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 3573
98.4%
Y 59
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3632
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 3573
98.4%
Y 59
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 3632
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3573
98.4%
Y 59
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3573
98.4%
Y 59
 
1.6%